# Scrapfly publishes guide on scraping DHL tracking data

> Scrapfly released a blog post detailing how to extract DHL parcel tracking status and shipment events using Python, including XHR analysis and API usage.

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- Beat: Extraction & Parsing · Evidence: Primary source · Type/significance: analysis/2 · First seen: 2026-09-11T23:30:22.728879+00:00 · Updated: 2026-09-11T23:30:22.728879+00:00 · Edition: 2026-11-05
- Framing: model-written (headline, standfirst, why it matters, tags); source facts deterministic

## Briefing
- Scrapfly: Scrapfly released a blog post detailing how to extract DHL parcel tracking status and shipment events using Python, including XHR analysis and API usage.

## Why it matters
This guide provides a practical reference for developers needing to integrate DHL tracking into logistics or e-commerce workflows. It covers both scraping the web interface and using the official API, offering a balanced approach that respects rate limits and data accuracy. The focus on event normalization and response classification helps avoid common pitfalls in tracking data extraction.

## Sources
- Primary source · Scrapfly · 2026-09-11 — [How to Scrape DHL Tracking Status and Shipment Events](https://scrapfly.io/blog/posts/how-to-scrape-dhl)

## Watch next
Will Scrapfly expand this guide to cover other major carriers like FedEx or UPS?

Topics: Scrapfly, DHL, dhl, tracking, python, api, web-scraping, logistics

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